Build Better Strategies! Part 4: Machine Learning

Deep Blue was the first computer that won a chess world championship. That was 1996, and it took 20 years until another program, AlphaGo, could defeat the best human Go player. Deep Blue was a model based system with hardwired chess rules. AlphaGo is a data-mining system, a deep neural network trained with thousands of Go games. Not improved hardware, but a breakthrough in software was essential for the step from beating top Chess players to beating top Go players. 
   In this 4th part of the mini-series we’ll look into the data mining approach for developing trading strategies. This method does not care about market mechanisms. It just scans price curves or other data sources for predictive patterns. Machine learning or “Artificial Intelligence” is not always involved in data-mining strategies. In fact the most popular – and surprisingly profitable – data mining method works without any fancy neural networks or support vector machines. Continue reading “Build Better Strategies! Part 4: Machine Learning”

Is “Scalping” Irrational?

Clients often ask for strategies that trade on very short time frames. Some are possibly inspired by “I just made $2000 in 5 minutes” stories on trader forums. Others have heard of High Frequency Trading: the higher the frequency, the better must be the trading! The Zorro developers had been pestered for years until they finally implemented tick histories and millisecond time frames. Totally useless features? Or has short term algo trading indeed some quantifiable advantages? An experiment for looking into that matter produced a surprising result. Continue reading “Is “Scalping” Irrational?”